Noradrenergic alpha-2a receptor stimulation enhances prediction error signaling and updating of attention sets in anterior cingulate cortex and striatum
Bibliographic record
Abstract
The noradrenergic system is believed to support behavioral flexibility. A possible source mediating improved flexibility are α2A adrenoceptors (α2AR) in prefrontal cortex (PFC) or the anterior cingulate cortex (ACC). We tested this hypothesis by stimulating α2ARs using Guanfacine during attentional set shifting in male nonhuman primates. We found that α2AR stimulation improved learning from errors and updating attention sets. Neural recordings in the ACC, dorsolateral PFC, and the striatum showed that α2AR stimulation selectively enhanced neural signaling of prediction errors in neurons of the ACC and the striatum, but not in dlPFC. This modulation was accompanied by enhanced encoding of attended target features and particularly apparent in putative fast-spiking interneurons, pointing to an interneuron mediated mechanism of α2AR action. These results reveal that α2A receptors are part of the causal chain of flexibly updating attention sets through an enhancement of outcomes and prediction error signaling in ACC and striatum. How noradrenergic modulation could support the flexible switching of cognitive states in primates is not fully understood. Here authors show that alpha-2A noradrenergic action causally enhances cognitive flexibility by enhancing prediction error signaling and neural coding of attended target features in anterior cingulate cortex and the anterior striatum.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".